Kurzfassung

We are presenting a new method to unwrap the phase from irregularly sampled differential SAR interferograms. Often such interferograms are used to observe land surface deformation in the order of centimeters over long time intervals, say up to years. However, in vegetated regions, the surface tends to decorrelate within this time frame and complicates a quantitative long term analysis. This is especially true for the short C-band wavelength of the space borne sensor ERS, the primary data source for radar interferometry. We are presenting a variation of Costantini's Minimum Cost Flow method, that avoids low coherence areas and uses isolated man made or natural point scattering objects instead in order to derive the deformation parameters of large scale land surface changes. The method implies automatic selection of stable targets, analysis of their quality, unwrapping of the target phases. The paper focuses on the phase unwrapping method, an adapted version of the minimum cost flow approach. Results are presented both from simulation and from a sample data set over a land subsidence area.